Bharat Book Bureau

Milk and Dairy Products in India - Production, Consumption and Exports Report

Till about year 2000, India was not on the radar screen of most international dairy companies, since India was neither a major importer nor an exporter of dairy products. Through the 70’s, 80’s and 90’s India used to take some milk powder and butter oil as aid. Exports from India were insignificantly small. From 2000 onwards, Indian dairy products, particularly milk powder, casein, whey products and ghee started making their presence felt in global markets.

The decade of 2000-10 will be recorded in dairy history as the decade of exports. But the next decade will be different. Signs of change are already visible. India is finding it difficult to sustain  exports. The day is not far when India will become a net importer of dairy products,particularly of dairy fats.

India’s milk production will grow at about 3 per cent per annum in spite of difficulties due to stagnant livestock herd size and shortage of fodder. Due to increasing population, per capita availability of milk will increase by only about 1.5 per cent per annum. For an economy growing at about 8 per cent per annum, this increase in availability will be grossly inadequate.

Introduction

India is the largest producer of milk producing more than 100 million tons of milk per annum. Yet, her per capita milk consumption is around 250 g per day.

India has a population of more than 1 billion with diverse food habits, cultures, traditions and religions. Regional variations within the country can be mind boggling. On one hand, the country has plains with long tradition of milk production and consumption. On the other hand, there are forest and hilly regions with no tradition of dairying. Most of coastal belts also do not have much of dairy tradition.

Cow is holy for Hindus who make up more than 80 per cent of the population of India. Buffalo enjoys no such holy status. Cow slaughter is banned in many states of India. There are no restrictions on buffalo culling.

All this makes India a very complex dairy country.

Production growing at only 3 per cent and consumption growing at more than double the rate is obviously going to lead to a mismatch between demand and supply. This will create opportunities for international dairy companies.

On one hand, India is expected to enter the international market with demand for commodities like skimmed milk powder and butter oil. On the other hand, growing prosperity and fast growth of organized modern retail and western style fast food outlets will lead to increased consumption of products like cheese and table butter. This will throw up opportunities for branded dairy products to enter this huge market of more than a billion people.

Helping international companies understand the dairy scenario of India from a macro-level perspective is the prime objective of this study. Facts and statistics, instead of opinions and impressions, are the key building blocks of this report.

During the study, we have tried, as far as possible, to rely on official data from some department / ministry / agency / directorate of government of India. This poses a problem since government agencies of India are slow in releasing data. For example, Director General of Commercial Intelligence & Statistics, Kolkata (responsible for compiling data on India’s imports and exports) had till the end of April 2008 released monthly export data in respect of only August 2007. Department of Animal Husbandry’s latest data is given in their Handbook released in December 2006, which gives data only for financial year ended on March 2006.

Inadequacy of official data is a perennial problem with most developing countries. Fortunately, in case of India the problem is not as severe. India has one of the oldest and most reliable census systems in the world. India conducts a fairly reliable livestock survey regularly. Data on economic fundamentals is extremely detailed and easily available. Trade data collection system of India is better than of most developing countries and is much more reliable than of most non-democratic countries.

Separating the useful and relevant from irrelevant and useless is always a challenge. It is more when so when one has an ocean of data (parts of which may be a bit old). This is a challenge that we are able to undertake with our long experience in India and Indian dairy / livestock industry in particular. We have our ear on the ground in India. We understand the dynamics of fast-changing India. We use the historical data provided by government agencies and rely on our experience and insightful expertise to see trends that others notice much later.

We hope that the study helps you get a macro-level understanding of the dairy scenario in India. This may however not answer all the queries that you may have. We look forward to conducting in-depth micro-level studies related to Indian dairy industry for you based on your  requirements.

For more information kindly visit:http://www.bharatbook.com/Market-Research-Reports/Milk-and-Dairy-Products-in-India-Production-Consumption-and-Exports.html

The Vietnam Infrastrucure Report has been researched at source, and features latest-available data covering public procurement and spending on all major infrastructure and construction projects, including transportation and logistics by land, sea and air; power plants and utilities, and commercial construction and property development; 5-year industry forecasts through end-2011; company rankings and competitive landscapes covering leading multinational and national contractors; and analysis of latest industry trends, opportunities, projects and regulatory changes..

Vietnamese Infrastructure Reports provide industry professionals and strategists, sector analysts, investors, trade associations and regulatory bodies with independent forecasts and competitive intelligence on Vietnamese infrastructure and construction.

Independent 5 year Infrastructure industry forecasts for Vietnam.
Original Infrastructure market research and Infrastructure sector trend analysis for Vietnam.
Competitive intelligence, Vietnamese Infrastructure company rankings and SWOT analyses on international and domestic Infrastructure companies in Vietnam.

Key Benefits of Reports

Benchmark It’s Independent 5-year Infrastructure Industry Forecasts to test other views – a key input for successful budgetary and planning in the Vietnamese strategic Infrastructure market.

Target Business Opportunities & Risks in the Vietnamese Infrastructure Sector through our reviews of latest industry trends, regulatory changes and major deals, projects and investments in Vietnam.

Exploit the Latest Competitive Infrastructure Intelligence & company SWOTS on your competitors and peers through company rankings by sales, market share and ownership structure – includes multi-national and national companies

Coverage

Executive Summary

Summary of It’s key industry forecasts, views and trend analysis covering Infrastructure and construction, regulatory changes, major investments and projects, and significant multinational and national company developments.

Industry Trends And Developments

Analysis of latest projects across the Infrastructure sector – transport, utilities, commercial construction – including market overview which provides an outline of the key elements driving developments.

Industry Environment Ranking

It’s regional comparative analysis of the Infrastructure sector, evaluating sector-specific issues within the broader Country Risk context, including each state’s overall economic and political stability.

SWOT Analysis

SWOT (strengths, weaknesses, opportunities, threats) of the state’s business environment, Infrastructure sector, politics and economics, which carefully evaluates the short- and medium-term issues facing the industry.

It 5-Year Industry & Macro Forecast

Historic data series and 5-year forecasts to end-2011 for all key industry and economic indicators, supported by explicit assumptions, plus analysis of key risks to the main forecast. Indicators include:
Industry value (US$bn); contribution to GDP (%); Infrastructure, procurement and spending on major projects (US$bn); cement production (mn tonnes); housing completions (‘000 units), sector employment (‘000); population growth (mn); nominal GDP (US$bn); real GDP growth (%); industrial production index (% y-o-y average); consumer price index (%y-o-y average); current account (US$bn), external debt (US$bn).

Competitive Landscape & Company Profiles

Comparative company analyses and rankings by sales, % market share, employees, registration date and ownership structure. Company profiles include fully researched senior executives and contact details, business activity and leading products and services.

To know more and to buy a copy of your report feel free to visit:  http://www.bharatbook.com/productdetail.asp?id=16239

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Contact us at:
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Independent 5 year Infrastructure industry forecasts for Kuwait.
Original Infrastructure market research and Infrastructure sector trend analysis for Kuwait.
Competitive intelligence, Kuwaiti Infrastructure company rankings and SWOT analyses on international and domestic Infrastructure companies in Kuwait.

The Kuwait Infrastrucure Report has been researched at source, and features latest-available data covering public procurement and spending on all major infrastructure and construction projects, including transportation and logistics by land, sea and air; power plants and utilities, and commercial construction and property development; 5-year industry forecasts through end-2011; company rankings and competitive landscapes covering leading multinational and national contractors; and analysis of latest industry trends, opportunities, projects and regulatory changes..

Kuwaiti Infrastructure Reports provide industry professionals and strategists, sector analysts, investors, trade associations and regulatory bodies with independent forecasts and competitive intelligence on Kuwaiti infrastructure and construction.

Key Benefits of Reports

Benchmark It’s Independent 5-year Infrastructure Industry Forecasts to test other views – a key input for successful budgetary and planning in the Kuwaiti strategic Infrastructure market.

Target Business Opportunities & Risks in the Kuwaiti Infrastructure Sector through our reviews of latest industry trends, regulatory changes and major deals, projects and investments in Kuwait.

Exploit the Latest Competitive Infrastructure Intelligence & company SWOTS on your competitors and peers through company rankings by sales, market share and ownership structure – includes multi-national and national companies

Coverage

Executive Summary

Summary of It’s key industry forecasts, views and trend analysis covering Infrastructure and construction, regulatory changes, major investments and projects, and significant multinational and national company developments.

Industry Trends And Developments

Analysis of latest projects across the Infrastructure sector – transport, utilities, commercial construction – including market overview which provides an outline of the key elements driving developments.

Industry Environment Ranking

It’s regional comparative analysis of the Infrastructure sector, evaluating sector-specific issues within the broader Country Risk context, including each state’s overall economic and political stability.

SWOT Analysis

SWOT (strengths, weaknesses, opportunities, threats) of the state’s business environment, Infrastructure sector, politics and economics, which carefully evaluates the short- and medium-term issues facing the industry.

It 5-Year Industry & Macro Forecast

Historic data series and 5-year forecasts to end-2011 for all key industry and economic indicators, supported by explicit assumptions, plus analysis of key risks to the main forecast. Indicators include:
Industry value (US$bn); contribution to GDP (%); Infrastructure, procurement and spending on major projects (US$bn); cement production (mn tonnes); housing completions (‘000 units), sector employment (‘000); population growth (mn); nominal GDP (US$bn); real GDP growth (%); industrial production index (% y-o-y average); consumer price index (%y-o-y average); current account (US$bn), external debt (US$bn).

Competitive Landscape & Company Profiles

Comparative company analyses and rankings by sales, % market share, employees, registration date and ownership structure. Company profiles include fully researched senior executives and contact details, business activity and leading products and services.

To know more and to buy a copy of your report feel free to visit:  http://www.bharatbook.com/productdetail.asp?id=16223

Or

Contact us at:
Bharat Book Bureau
Tel: +91 22 2757 8668
Fax: +91 22 2757 9131
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Blog: http://bharatbookresearch.blogspot.com

2006-2011 World Outlook for Phosphorus Trichloride (chloride, 100 Percent PCl3)

WHAT IS LATENT DEMAND AND THE P.I.E.?

The concept of latent demand is rather subtle. The term latent typically refers to something that is dormant, not observable, or not yet realized. Demand is the notion of an economic quantity that a target population or market requires under different assumptions of price, quality, and distribution, among other factors. Latent demand, therefore, is commonly defined by economists as the industry earnings of a market when that market becomes accessible and attractive to serve by competing firms. It is a measure, therefore, of potential industry earnings (P.I.E.) or total revenues (not profit) if a market is served in an efficient manner. It is typically expressed as the total revenues potentially extracted by firms. The “market” is defined at a given level in the value chain. There can be latent demand at the retail level, at the wholesale level, the manufacturing level, and the raw materials level (the P.I.E. of higher levels of the value chain being always smaller than the P.I.E. of levels at lower levels of the same value chain, assuming all levels maintain minimum profitability).

The latent demand for phosphorus trichloride (chloride, 100 percent PCl3) is not actual or historic sales. Nor is latent demand future sales. In fact, latent demand can be lower either lower or higher than actual sales if a market is inefficient (i.e., not representative of relatively competitive levels). Inefficiencies arise from a number of factors, including the lack of international openness, cultural barriers to consumption, regulations, and cartel-like behavior on the part of firms. In general, however, latent demand is typically larger than actual sales in a country market.

For reasons discussed later, this report does not consider the notion of “unit quantities”, only total latent revenues (i.e., a calculation of price times quantity is never made, though one is implied). The units used in this report are U.S. dollars not adjusted for inflation (i.e., the figures incorporate inflationary trends) and not adjusted for future dynamics in exchange rates (i.e., the figures reflect average exchange rates over recent history). If inflation rates or exchange rates vary in a substantial way compared to recent experience, actually sales can also exceed latent demand (when expressed in U.S. dollars, not adjusted for inflation). On the other hand, latent demand can be typically higher than actual sales as there are often distribution inefficiencies that reduce actual sales below the level of latent demand.

As mentioned in the introduction, this study is strategic in nature, taking an aggregate and long-run view, irrespective of the players or products involved. If fact, all the current products or services on the market can cease to exist in their present form (i.e., at a brand-, R&D specification, or corporate-image level) and all the players can be replaced by other firms (i.e., via exits, entries, mergers, bankruptcies, etc.), and there will still be an international latent demand for phosphorus trichloride (chloride, 100 percent PCl3) at the aggregate level. Product and service offering details, and the actual identity of the players involved, while important for certain issues, are relatively unimportant for estimates of latent demand.

THE METHODOLOGY

In order to estimate the latent demand for phosphorus trichloride (chloride, 100 percent PCl3) on a worldwide basis, I used a multi-stage approach. Before applying the approach, one needs a basic theory from which such estimates are created. In this case, I heavily rely on the use of certain basic economic assumptions. In particular, there is an assumption governing the shape and type of aggregate latent demand functions. Latent demand functions relate the income of a country, city, state, household, or individual to realized consumption. Latent demand (often realized as consumption when an industry is efficient), at any level of the value chain, takes place if an equilibrium in realized. For firms to serve a market, they must perceive a latent demand and be able to serve that demand at a minimal return. The single most important variable determining consumption, assuming latent demand exists, is income (or other financial resources at higher levels of the value chain). Other factors that can pivot or shape demand curves include external or exogenous shocks (i.e., business cycles), and or changes in utility for the product in question.

Ignoring, for the moment, exogenous shocks and variations in utility across countries, the aggregate relation between income and consumption has been a central theme in economics. The figure below concisely summarizes one aspect of problem. In the 1930s, John Meynard Keynes conjectured that as incomes rise, the average propensity to consume would fall. The average propensity to consume is the level of consumption divided by the level of income, or the slope of the line from the origin to the consumption function. He estimated this relationship empirically and found it to be true in the short-run (mostly based on cross-sectional data). The higher the income, the lower the average propensity to consume. This type of consumption function is labeled “A” in the figure below (note the rather flat slope of the curve). In the 1940s, another macroeconomist, Simon Kuznets, estimated long-run consumption functions which indicated that the marginal propensity to consume was rather constant (using time series data across countries). This type of consumption function is show as “B” in the figure below (note the higher slope and zero-zero intercept). The average propensity to consume is constant.

Is it declining or is it constant? A number of other economists, notably Franco Modigliani and Milton Friedman, in the 1950s (and Irving Fisher earlier), explained why the two functions were different using various assumptions on intertemporal budget constraints, savings, and wealth. The shorter the time horizon, the more consumption can depend on wealth (earned in previous years) and business cycles. In the long-run, however, the propensity to consume is more constant. Similarly, in the long run, households, industries or countries with no income eventually have no consumption (wealth is depleted). While the debate surrounding beliefs about how income and consumption are related and interesting, in this study a very particular school of thought is adopted. In particular, we are considering the latent demand for phosphorus trichloride (chloride, 100 percent PCl3) across some 230 countries. The smallest have fewer than 10,000 inhabitants. I assume that all of these counties fall along a “long-run” aggregate consumption function. This long-run function applies despite some of these countries having wealth, current income dominates the latent demand for phosphorus trichloride (chloride, 100 percent PCl3). So, latent demand in the long-run has a zero intercept. However, I allow firms to have different propensities to consume (including being on consumption functions with differing slopes, which can account for differences in industrial organization, and end-user preferences).

Given this overriding philosophy, I will now describe the methodology used to create the latent demand estimates for phosphorus trichloride (chloride, 100 percent PCl3). Since ICON Group has asked me to apply this methodology to a large number of categories, the rather academic discussion below is general and can be applied to a wide variety of categories, not just phosphorus trichloride (chloride, 100 percent PCl3).

Step 1. Product Definition and Data Collection

Any study of latent demand across countries requires that some standard be established to define “efficiently served”. Having implemented various alternatives and matched these with market outcomes, I have found that the optimal approach is to assume that certain key countries are more likely to be at or near efficiency than others. These countries are given greater weight than others in the estimation of latent demand compared to other countries for which no known data are available. Of the many alternatives, I have found the assumption that the world’s highest aggregate income and highest income-per-capita markets reflect the best standards for “efficiency”. High aggregate income alone is not sufficient (i.e., China has high aggregate income, but low income per capita and can not assumed to be efficient). Aggregate income can be operationalized in a number of ways, including gross domestic product (for industrial categories), or total disposable income (for household categories; population times average income per capita, or number of households times average household income per capita). Brunei, Nauru, Kuwait, and Lichtenstein are examples of countries with high income per capita, but not assumed to be efficient, given low aggregate level of income (or gross domestic product); these countries have, however, high incomes per capita but may not benefit from the efficiencies derived from economies of scale associated with large economies. Only countries with high income per capita and large aggregate income are assumed efficient. This greatly restricts the pool of countries to those in the OECD (Organization for Economic Cooperation and Development), like the United States, or the United Kingdom (which were earlier than other large OECD economies to liberalize their markets).

The selection of countries is further reduced by the fact that not all countries in the OECD report industry revenues at the category level. Countries that typically have ample data at the aggregate level that meet the efficiency criteria include the United States, the United Kingdom and in some cases France and Germany.

Latent demand is therefore estimated using data collected for relatively efficient markets from independent data sources (e.g. Euromonitor, Mintel, Thomson Financial Services, the U.S. Industrial Outlook, the World Resources Institute, the Organization for Economic Cooperation and Development, various agencies from the United Nations, industry trade associations, the International Monetary Fund, and the World Bank). Depending on original data sources used, the definition of “phosphorus trichloride (chloride, 100 percent PCl3)” is established. In the case of this report, the data were reported at the aggregate level, with no further breakdown or definition. In other words, any potential product or service that might be incorporated within phosphorus trichloride (chloride, 100 percent PCl3) falls under this category. Public sources rarely report data at the disaggregated level in order to protect private information from individual firms that might dominate a specific product-market. These sources will therefore aggregate across components of a category and report only the aggregate to the public. While private data are certainly available, this report only relies on public data at the aggregate level without reliance on the summation of various category components. In other words, this report does not aggregate a number of components to arrive at the “whole”. Rather, it starts with the “whole”, and estimates the whole for all countries and the world at large (without needing to know the specific parts that went into the whole in the first place).

Step 2. Filtering and Smoothing

Based on the aggregate view of phosphorus trichloride (chloride, 100 percent PCl3) as defined above, data were then collected for as many similar countries as possible for that same definition, at the same level of the value chain. This generates a convenience sample of countries from which comparable figures are available. If the series in question do not reflect the same accounting period, then adjustments are made. In order to eliminate short-term effects of business cycles, the series are smoothed using an 2 year moving average weighting scheme (longer weighting schemes do not substantially change the results). If data are available for a country, but these reflect short-run aberrations due to exogenous shocks (such as would be the case of beef sales in a country stricken with foot and mouth disease), these observations were dropped or “filtered” from the analysis.

Step 3. Filling in Missing Values

In some cases, data are available for countries on a sporadic basis. In other cases, data from a country may be available for only one year. From a Bayesian perspective, these observations should be given greatest weight in estimating missing years. Assuming that other factors are held constant, the missing years are extrapolated using changes and growth in aggregate national income. Based on the overriding philosophy of a long-run consumption function (defined earlier), countries which have missing data for any given year, are estimated based on historical dynamics of aggregate income for that country.

Step 4. Varying Parameter, Non-linear Estimation

Given the data available from the first three steps, the latent demand in additional countries is estimated using a “varying-parameter cross-sectionally pooled time series model”. Simply stated, the effect of income on latent demand is assumed to be constant across countries unless there is empirical evidence to suggest that this effect varies (i.e., . the slope of the income effect is not necessarily same for all countries). This assumption applies across countries along the aggregate consumption function, but also over time (i.e., not all countries are perceived to have the same income growth prospects over time and this effect can vary from country to country as well). Another way of looking at this is to say that latent demand for phosphorus trichloride (chloride, 100 percent PCl3) is more likely to be similar across countries that have similar characteristics in terms of economic development (i.e., African countries will have similar latent demand structures controlling for the income variation across the pool of African countries).

This approach is useful across countries for which some notion of non-linearity exists in the aggregate cross-country consumption function. For some categories, however, the reader must realize that the numbers will reflect a country’s contribution to global latent demand and may never be realized in the form of local sales. For certain country-category combinations this will result in what at first glance will be odd results. For example, the latent demand for the category “space vehicles” will exist for “Togo” even though they have no space program. The assumption is that if the economies in these countries did not exist, the world aggregate for these categories would be lower. The share attributed to these countries is based on a proportion of their income (however small) being used to consume the category in question (i.e., perhaps via resellers).

Step 5. Fixed-Parameter Linear Estimation

Nonlinearities are assumed in cases where filtered data exist along the aggregate consumption function. Because the world consists of more than 200 countries, there will always be those countries, especially toward the bottom of the consumption function, where non-linear estimation is simply not possible. For these countries, equilibrium latent demand is assumed to be perfectly parametric and not a function of wealth (i.e., a country’s stock of income), but a function of current income (a country’s flow of income). In the long run, if a country has no current income, the latent demand for phosphorus trichloride (chloride, 100 percent PCl3) is assumed to approach zero. The assumption is that wealth stocks fall rapidly to zero if flow income falls to zero (i.e., countries which earn low levels of income will not use their savings, in the long run, to demand phosphorus trichloride (chloride, 100 percent PCl3)). In a graphical sense, for low income countries, latent demand approaches zero in a parametric linear fashion with a zero-zero intercept. In this stage of the estimation procedure, low-income countries are assumed to have a latent demand proportional to their income, based on the country closest to it on the aggregate consumption function.

Step 6. Aggregation and Benchmarking

Based on the models described above, latent demand figures are estimated for all countries of the world, including for the smallest economies. These are then aggregated to get world totals and regional totals. To make the numbers more meaningful, regional and global demand averages are presented. Figures are rounded, so minor inconsistencies may exist across tables.

Step 7. Latent Demand Density: Allocating Across Cities

With the advent of a “borderless world”, cities become a more important criteria in prioritizing markets, as opposed to regions, continents, or countries. This report also covers the world’s top 2000 cities. The purpose is to understand the density of demand within a country and the extent to which a city might be used as a point of distribution within its region. From an economic perspective, however, a city does not represent a population within rigid geographical boundaries. To an economist or strategic planner, a city represents an area of dominant influence over markets in adjacent areas. This influence varies from one industry to another, but also from one period of time to another.

Similar to country-level data, the reader needs to realize that latent demand allocated to a city may or may not represent real sales. For many items, latent demand is clearly observable in sales, as in the case for food or housing items. Consider, again, the category “satellite launch vehicles.” Clearly, there are no launch pads in most cities of the world. However, the core benefit of the vehicles (e.g. telecommunications, etc.) is “consumed” by residents or industries within the world’s cities. Without certain cities, in other words, the world market for satellite launch vehicles would be lower for the world in general. One needs to allocate, therefore, a portion of the worldwide economic demand for launch vehicles to regions, countries and cities. This report takes the broader definition and considers, therefore, a city as a part of the global market. I allocate latent demand across areas of dominant influence based on the relative economic importance of cities within its home country, within its region and across the world total. Not all cities are estimated within each country as demand may be allocated to adjacent areas of influence. Since some cities have higher economic wealth than others within the same country, a city’s population is not generally used to allocate latent demand. Rather, the level of economic activity of the city vis-à-vis others.

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Indian Logistics Sector: Strategic Assessment of Key Elements and Opportunities

This report by Infolitics and HS&SL provides detailed opportunity assessment of key elements in the Indian Logistics sector.

Bharatbook is proud to announce the addiction of new report  on ” Indian Logistics Sector: Strategic Assessment of Key Elements and Opportunities” (http://www.bharatbook.com/Market-Research-Reports/Indian-Logistics-Sector-Strategic-Assessment-of-Key-Elements-and-Opportunities.html)

This report by Infolitics and HS&SL provides detailed opportunity assessment of key elements in the Indian Logistics sector. The report starts with identification of key strategic elements of the value chain / supply chain in Chapter 2. Chapter 3 provides overview of strategic elements. Chapter 4 discusses each element in-depth to understand the sector opportunities in detail. The details covered include overview of the element in Indian logistics context, importance of the element, market analysis, stakeholders, end-user analysis, competition assessment, needs and future trend, investments done in the sector, rules, and opportunities in the sector. This is supported by financial analysis done in Chapter 5 of the report. Financial analysis also includes typical investments, expenditure, ROI etc. Chapter 6 compares various sector opportunities by using a standard benchmark of factors spanning across possible ROI, technical and financial requirements, competition assessment and difficulty of implementation. This is presented as an Opportunity Matrix.

This report is one step ahead in understanding the strategic elements of Indian logistics sector as it delves into each strategic element and identifies opportunities, rather than skimming over the logistics scenario by reporting facts, figures and new developments. The report provides insights which can be used to understand the sector and directly assess a particular sector opportunity.

Scope
The report covers opportunity assessment in key elements of the Indian logistics sector. The ten strategic sectors identified in the report include:
1. Air Cargo Logistics
2. Cold Chain / Cold Storage
3. Custom Bonded Warehouse
4. Custom House Agents (CHA)
5. Distribution Centre (DC)
6. ICD / CFS
7. Project Cargo
8. Road Transport Service Provider
9. Sea Ports
10. Warehouse

Containerization and rail based logistics are other major strategic growth areas of Indian logistics sector and these are studied under various strategic elements mentioned above, wherever they impact.

Reasons to purchase

A strategic report of first of its kind to cover opportunities in key elements of Indian logistics sector
106 pages packed with information, insights and analysis on strategic assessment of key elements of Indian Logistics sector
47 tables & 16 charts
Statistics from reliable official sources
Statistics and trends based on analysis of data and insights gained by interviews with existing market players / policy decision makers
Holistic view taking all factors into account
Benchmarking of various sectors on broad level parameters to provide relative assessment of opportunities

Table of Contents

1 Executive Summary
2 Critical Elements of Indian Logistics Sector
2.1 Structural Elements of Indian Logistics Industry
2.1.1 Cargo Import Steps and Important Logistics Elements
2.1.2 Cargo Export Steps and Important Logistics Elements
2.1.3 Other Logistics Elements
3 Strategic Growth Areas of Indian Logistics Sector
3.1 Cold Chain / Cold Storage
3.2 Air Cargo Logistics
3.3 Warehousing in India
3.4 Custom Bonded Warehouse
3.5 Distribution Centre (DC)
3.6 Road Transport Service Provider
3.7 Custom House Agents (CHA)
3.8 Project Cargo
3.9 ICD / CFS
3.10 Sea Ports
4 Analysis of Opportunities
4.1 Cold Chain Operations
4.1.1 National Opportunity Assessment and Value Chain
4.1.2 Breadth of Cold Chain Operations in India
4.1.3 Cold Storage Types and Storage Needs for various Commodities in India
4.1.4 Cold Storage – Components, Commodities to Store, and Operations
4.1.5 Sources of Finance for Cold Storage in India
4.1.6 Optimal Cold Storage Design
4.2 Air Cargo Logistics in India
4.2.1 Prominent Indian Airports – Volume and Volume Growth
4.2.2 Prominent Indian Airports – International Cargo
4.2.3 Cold Storage facility for Exports at Air Cargo Hubs
4.3 Warehousing in India
4.3.1 Warehousing Overview, Needs, Classification by Ownership and Services
4.3.2 Warehousing Documents
4.3.3 Warehousing in India – Stakeholders and Roles
4.3.4 Warehousing Opportunity in various Sectors
4.3.5 Pharmaceutical Warehousing and C&F
4.3.6 Value added services in Warehousing
4.4 Custom Bonded Warehouse – Need in India and Opportunity Assessment
4.4.1 Overview of Custom Bonded Warehouse
4.4.2 Opportunity Assessment for Custom Bonded Warehouse
4.5 Distribution Centre (DC)
4.5.1 Opportunity Assessment
4.6 Road Transport Service Provider – Working Models in India, Revenues and Opportunity Assessment
4.6.1 Overview of Business
4.6.2 Supply Chain (Interrelationships) in Indian Road Transport Service Industry
4.6.3 Revenue Earnings – Sources and Potential
4.6.4 Opportunity Assessment
4.7 Customs House Agent (CHA) – Market, Customer and Opportunity Assessment
4.7.1 Market Analysis
4.7.2 Customer Analysis: End-users of CHA, Needs and Future Trends
4.7.3 Opportunity Assessment
4.8 Project Cargo – Working Model in India, Market Size & Growth, and Critical Success Factors
4.8.1 Operating Model in Project Cargo Business – The Predominant Model
4.8.2 Market Analysis – Size and Growth of Market
4.8.3 Critical Success Factors of CHA Business
4.9 ICD/CFS – Market Analysis and Opportunity Assessment in India
4.9.1 Market Analysis of ICDs / CFSs
4.9.2 Opportunity Assessment – Container Traffic and EXIM
4.10 Sea Ports – Opportunity Assessment in Containerization and Infrastructure Growth
4.10.1 Containerization – Market Size & Growth, Opportunities / Potential and Expected Future Trends
4.10.2 Sea Port Infrastructure Growth
5 Financials
5.1 Cold Storage – Investment, Expenditure, Revenues and Profitability Assessment through Scenario Analysis
5.1.1 Cold Storage Investment – Subsidized Investment Estimations
5.1.2 Cold Storage Revenues – Break-up and Estimations for Trading / Renting
5.1.3 Cold Storage Expenditure – Major Heads and Prevailing Rates
5.1.4 Projected Profitability of Cold Storage based on Scenario Analysis
5.2 Warehousing – Investment, Expenditure, Revenues and Profitability Assessment through Scenario Analysis
5.2.1 Investment in a Warehouse
5.2.2 Projected Revenue Earnings from a Warehouse
5.2.3 Expenditure – Major Heads and Prevailing Rates
5.2.4 Projected Profitability of a Warehouse based on Scenario Analysis
5.3 Custom Bonded Warehouse - Investment, Expenditure, Revenues and Profitability Assessment
5.3.1 Investment
5.3.2 Setting up a Custom Bonded Warehouse
5.3.3 Revenues and Profitability
5.4 Custom House Agent (CHA) - Investment, Expenditure, Revenues and Profitability Assessment
5.4.1 Investment in setting-up CHA Business
5.4.2 CHA Revenues
5.4.3 CHA Profitability
5.5 Project Cargo - Revenues and Profitability Assessment
5.5.1 Revenue Sources in Project Cargo Business
5.5.2 Profitability of Project Cargo Business
5.6 Road Transport Service Provider - Investment, Expenditure, Revenues and Profitability Assessment

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2006-2011 World Outlook for Sodium Chlorate (100 Percent NaClO3)

WHAT IS LATENT DEMAND AND THE P.I.E.?

The concept of latent demand is rather subtle. The term latent typically refers to something that is dormant, not observable, or not yet realized. Demand is the notion of an economic quantity that a target population or market requires under different assumptions of price, quality, and distribution, among other factors. Latent demand, therefore, is commonly defined by economists as the industry earnings of a market when that market becomes accessible and attractive to serve by competing firms. It is a measure, therefore, of potential industry earnings (P.I.E.) or total revenues (not profit) if a market is served in an efficient manner. It is typically expressed as the total revenues potentially extracted by firms. The “market” is defined at a given level in the value chain. There can be latent demand at the retail level, at the wholesale level, the manufacturing level, and the raw materials level (the P.I.E. of higher levels of the value chain being always smaller than the P.I.E. of levels at lower levels of the same value chain, assuming all levels maintain minimum profitability).

The latent demand for sodium chlorate (100 percent NaClO3) is not actual or historic sales. Nor is latent demand future sales. In fact, latent demand can be lower either lower or higher than actual sales if a market is inefficient (i.e., not representative of relatively competitive levels). Inefficiencies arise from a number of factors, including the lack of international openness, cultural barriers to consumption, regulations, and cartel-like behavior on the part of firms. In general, however, latent demand is typically larger than actual sales in a country market.

For reasons discussed later, this report does not consider the notion of “unit quantities”, only total latent revenues (i.e., a calculation of price times quantity is never made, though one is implied). The units used in this report are U.S. dollars not adjusted for inflation (i.e., the figures incorporate inflationary trends) and not adjusted for future dynamics in exchange rates (i.e., the figures reflect average exchange rates over recent history). If inflation rates or exchange rates vary in a substantial way compared to recent experience, actually sales can also exceed latent demand (when expressed in U.S. dollars, not adjusted for inflation). On the other hand, latent demand can be typically higher than actual sales as there are often distribution inefficiencies that reduce actual sales below the level of latent demand.

As mentioned in the introduction, this study is strategic in nature, taking an aggregate and long-run view, irrespective of the players or products involved. If fact, all the current products or services on the market can cease to exist in their present form (i.e., at a brand-, R&D specification, or corporate-image level) and all the players can be replaced by other firms (i.e., via exits, entries, mergers, bankruptcies, etc.), and there will still be an international latent demand for sodium chlorate (100 percent NaClO3) at the aggregate level. Product and service offering details, and the actual identity of the players involved, while important for certain issues, are relatively unimportant for estimates of latent demand.

THE METHODOLOGY

In order to estimate the latent demand for sodium chlorate (100 percent NaClO3) on a worldwide basis, I used a multi-stage approach. Before applying the approach, one needs a basic theory from which such estimates are created. In this case, I heavily rely on the use of certain basic economic assumptions. In particular, there is an assumption governing the shape and type of aggregate latent demand functions. Latent demand functions relate the income of a country, city, state, household, or individual to realized consumption. Latent demand (often realized as consumption when an industry is efficient), at any level of the value chain, takes place if an equilibrium in realized. For firms to serve a market, they must perceive a latent demand and be able to serve that demand at a minimal return. The single most important variable determining consumption, assuming latent demand exists, is income (or other financial resources at higher levels of the value chain). Other factors that can pivot or shape demand curves include external or exogenous shocks (i.e., business cycles), and or changes in utility for the product in question.

Ignoring, for the moment, exogenous shocks and variations in utility across countries, the aggregate relation between income and consumption has been a central theme in economics. The figure below concisely summarizes one aspect of problem. In the 1930s, John Meynard Keynes conjectured that as incomes rise, the average propensity to consume would fall. The average propensity to consume is the level of consumption divided by the level of income, or the slope of the line from the origin to the consumption function. He estimated this relationship empirically and found it to be true in the short-run (mostly based on cross-sectional data). The higher the income, the lower the average propensity to consume. This type of consumption function is labeled “A” in the figure below (note the rather flat slope of the curve). In the 1940s, another macroeconomist, Simon Kuznets, estimated long-run consumption functions which indicated that the marginal propensity to consume was rather constant (using time series data across countries). This type of consumption function is show as “B” in the figure below (note the higher slope and zero-zero intercept). The average propensity to consume is constant.

Is it declining or is it constant? A number of other economists, notably Franco Modigliani and Milton Friedman, in the 1950s (and Irving Fisher earlier), explained why the two functions were different using various assumptions on intertemporal budget constraints, savings, and wealth. The shorter the time horizon, the more consumption can depend on wealth (earned in previous years) and business cycles. In the long-run, however, the propensity to consume is more constant. Similarly, in the long run, households, industries or countries with no income eventually have no consumption (wealth is depleted). While the debate surrounding beliefs about how income and consumption are related and interesting, in this study a very particular school of thought is adopted. In particular, we are considering the latent demand for sodium chlorate (100 percent NaClO3) across some 230 countries. The smallest have fewer than 10,000 inhabitants. I assume that all of these counties fall along a “long-run” aggregate consumption function. This long-run function applies despite some of these countries having wealth, current income dominates the latent demand for sodium chlorate (100 percent NaClO3). So, latent demand in the long-run has a zero intercept. However, I allow firms to have different propensities to consume (including being on consumption functions with differing slopes, which can account for differences in industrial organization, and end-user preferences).

Given this overriding philosophy, I will now describe the methodology used to create the latent demand estimates for sodium chlorate (100 percent NaClO3). Since ICON Group has asked me to apply this methodology to a large number of categories, the rather academic discussion below is general and can be applied to a wide variety of categories, not just sodium chlorate (100 percent NaClO3).

Step 1. Product Definition and Data Collection

Any study of latent demand across countries requires that some standard be established to define “efficiently served”. Having implemented various alternatives and matched these with market outcomes, I have found that the optimal approach is to assume that certain key countries are more likely to be at or near efficiency than others. These countries are given greater weight than others in the estimation of latent demand compared to other countries for which no known data are available. Of the many alternatives, I have found the assumption that the world’s highest aggregate income and highest income-per-capita markets reflect the best standards for “efficiency”. High aggregate income alone is not sufficient (i.e., China has high aggregate income, but low income per capita and can not assumed to be efficient). Aggregate income can be operationalized in a number of ways, including gross domestic product (for industrial categories), or total disposable income (for household categories; population times average income per capita, or number of households times average household income per capita). Brunei, Nauru, Kuwait, and Lichtenstein are examples of countries with high income per capita, but not assumed to be efficient, given low aggregate level of income (or gross domestic product); these countries have, however, high incomes per capita but may not benefit from the efficiencies derived from economies of scale associated with large economies. Only countries with high income per capita and large aggregate income are assumed efficient. This greatly restricts the pool of countries to those in the OECD (Organization for Economic Cooperation and Development), like the United States, or the United Kingdom (which were earlier than other large OECD economies to liberalize their markets).

The selection of countries is further reduced by the fact that not all countries in the OECD report industry revenues at the category level. Countries that typically have ample data at the aggregate level that meet the efficiency criteria include the United States, the United Kingdom and in some cases France and Germany.

Latent demand is therefore estimated using data collected for relatively efficient markets from independent data sources (e.g. Euromonitor, Mintel, Thomson Financial Services, the U.S. Industrial Outlook, the World Resources Institute, the Organization for Economic Cooperation and Development, various agencies from the United Nations, industry trade associations, the International Monetary Fund, and the World Bank). Depending on original data sources used, the definition of “sodium chlorate (100 percent NaClO3)” is established. In the case of this report, the data were reported at the aggregate level, with no further breakdown or definition. In other words, any potential product or service that might be incorporated within sodium chlorate (100 percent NaClO3) falls under this category. Public sources rarely report data at the disaggregated level in order to protect private information from individual firms that might dominate a specific product-market. These sources will therefore aggregate across components of a category and report only the aggregate to the public. While private data are certainly available, this report only relies on public data at the aggregate level without reliance on the summation of various category components. In other words, this report does not aggregate a number of components to arrive at the “whole”. Rather, it starts with the “whole”, and estimates the whole for all countries and the world at large (without needing to know the specific parts that went into the whole in the first place).

Step 2. Filtering and Smoothing

Based on the aggregate view of sodium chlorate (100 percent NaClO3) as defined above, data were then collected for as many similar countries as possible for that same definition, at the same level of the value chain. This generates a convenience sample of countries from which comparable figures are available. If the series in question do not reflect the same accounting period, then adjustments are made. In order to eliminate short-term effects of business cycles, the series are smoothed using an 2 year moving average weighting scheme (longer weighting schemes do not substantially change the results). If data are available for a country, but these reflect short-run aberrations due to exogenous shocks (such as would be the case of beef sales in a country stricken with foot and mouth disease), these observations were dropped or “filtered” from the analysis.

Step 3. Filling in Missing Values

In some cases, data are available for countries on a sporadic basis. In other cases, data from a country may be available for only one year. From a Bayesian perspective, these observations should be given greatest weight in estimating missing years. Assuming that other factors are held constant, the missing years are extrapolated using changes and growth in aggregate national income. Based on the overriding philosophy of a long-run consumption function (defined earlier), countries which have missing data for any given year, are estimated based on historical dynamics of aggregate income for that country.

Step 4. Varying Parameter, Non-linear Estimation

Given the data available from the first three steps, the latent demand in additional countries is estimated using a “varying-parameter cross-sectionally pooled time series model”. Simply stated, the effect of income on latent demand is assumed to be constant across countries unless there is empirical evidence to suggest that this effect varies (i.e., . the slope of the income effect is not necessarily same for all countries). This assumption applies across countries along the aggregate consumption function, but also over time (i.e., not all countries are perceived to have the same income growth prospects over time and this effect can vary from country to country as well). Another way of looking at this is to say that latent demand for sodium chlorate (100 percent NaClO3) is more likely to be similar across countries that have similar characteristics in terms of economic development (i.e., African countries will have similar latent demand structures controlling for the income variation across the pool of African countries).

This approach is useful across countries for which some notion of non-linearity exists in the aggregate cross-country consumption function. For some categories, however, the reader must realize that the numbers will reflect a country’s contribution to global latent demand and may never be realized in the form of local sales. For certain country-category combinations this will result in what at first glance will be odd results. For example, the latent demand for the category “space vehicles” will exist for “Togo” even though they have no space program. The assumption is that if the economies in these countries did not exist, the world aggregate for these categories would be lower. The share attributed to these countries is based on a proportion of their income (however small) being used to consume the category in question (i.e., perhaps via resellers).

Step 5. Fixed-Parameter Linear Estimation

Nonlinearities are assumed in cases where filtered data exist along the aggregate consumption function. Because the world consists of more than 200 countries, there will always be those countries, especially toward the bottom of the consumption function, where non-linear estimation is simply not possible. For these countries, equilibrium latent demand is assumed to be perfectly parametric and not a function of wealth (i.e., a country’s stock of income), but a function of current income (a country’s flow of income). In the long run, if a country has no current income, the latent demand for sodium chlorate (100 percent NaClO3) is assumed to approach zero. The assumption is that wealth stocks fall rapidly to zero if flow income falls to zero (i.e., countries which earn low levels of income will not use their savings, in the long run, to demand sodium chlorate (100 percent NaClO3)). In a graphical sense, for low income countries, latent demand approaches zero in a parametric linear fashion with a zero-zero intercept. In this stage of the estimation procedure, low-income countries are assumed to have a latent demand proportional to their income, based on the country closest to it on the aggregate consumption function.

Step 6. Aggregation and Benchmarking

Based on the models described above, latent demand figures are estimated for all countries of the world, including for the smallest economies. These are then aggregated to get world totals and regional totals. To make the numbers more meaningful, regional and global demand averages are presented. Figures are rounded, so minor inconsistencies may exist across tables.

Step 7. Latent Demand Density: Allocating Across Cities

With the advent of a “borderless world”, cities become a more important criteria in prioritizing markets, as opposed to regions, continents, or countries. This report also covers the world’s top 2000 cities. The purpose is to understand the density of demand within a country and the extent to which a city might be used as a point of distribution within its region. From an economic perspective, however, a city does not represent a population within rigid geographical boundaries. To an economist or strategic planner, a city represents an area of dominant influence over markets in adjacent areas. This influence varies from one industry to another, but also from one period of time to another.

Similar to country-level data, the reader needs to realize that latent demand allocated to a city may or may not represent real sales. For many items, latent demand is clearly observable in sales, as in the case for food or housing items. Consider, again, the category “satellite launch vehicles.” Clearly, there are no launch pads in most cities of the world. However, the core benefit of the vehicles (e.g. telecommunications, etc.) is “consumed” by residents or industries within the world’s cities. Without certain cities, in other words, the world market for satellite launch vehicles would be lower for the world in general. One needs to allocate, therefore, a portion of the worldwide economic demand for launch vehicles to regions, countries and cities. This report takes the broader definition and considers, therefore, a city as a part of the global market. I allocate latent demand across areas of dominant influence based on the relative economic importance of cities within its home country, within its region and across the world total. Not all cities are estimated within each country as demand may be allocated to adjacent areas of influence. Since some cities have higher economic wealth than others within the same country, a city’s population is not generally used to allocate latent demand. Rather, the level of economic activity of the city vis-à-vis others.

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INTRODUCTION OVERVIEW
This study covers the world outlook for 100-percent natural crude glycerin across more than 200 countries. For each year reported, estimates are given for the latent demand, or potential industry earnings (P.I.E.), for the country in question (in millions of U.S. dollars), the percent share the country is of the region and of the globe. These comparative benchmarks allow the reader to quickly gauge a country vis-à-vis others. Using econometric models which project fundamental economic dynamics within each country and across countries, latent demand estimates are created. This report does not discuss the specific players in the market serving the latent demand, nor specific details at the product level. The study also does not consider short-term cyclicalities that might affect realized sales. The study, therefore, is strategic in nature, taking an aggregate and long-run view, irrespective of the players or products involved.

This study does not report actual sales data (which are simply unavailable, in a comparable or consistent manner in virtually all of the 230 countries of the world). This study gives, however, my estimates for the worldwide latent demand, or the P.I.E., for 100-percent natural crude glycerin. It also shows how the P.I.E. is divided across the world’s regional and national markets. For each country, I also show my estimates of how the P.I.E. grows over time (positive or negative growth). In order to make these estimates, a multi-stage methodology was employed that is often taught in courses on international strategic planning at graduate schools of business.

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Report on Indian Coal Industry

The Report elucidates facts about the Indian Coal industry supplemented by latest industry data and comprehensive analysis. Emphasis is laid on the following key subject matters to accomplish the report.

The characteristics of the industry (highly regulated, monopolistic, inelastic demand, seasonal supply, high risk industry, environmental issues and duty structure) are discussed in detail.
The industry structure along with the different mining methods and the regulatory framework within which the Industry players operate have been explained.
Global supply and consumption pattern for FY04-07 is provided along with the export volume of the leading coal exporting countries.
Category-wise Domestic Coal supply for the period CY02-07 is provided along with the geographical distribution of the coal reserves across the country. The production trend of the major coal suppliers for the period FY03-08 has been analysed.
Domestic Coal demand from different coal consuming sectors (power, steel, cement) for the period FY03-08 has been analysed.
Coal imports into the country from countries like Indonesia, China, South Africa, Australia have been presented in detail.
Projection on sector-wise demand for coal for FY08-10 is presented along with demand projections by other competent authorities (CIL’s Coal vision, ‘Expert Committee road map on coal reforms’).
The challenges and steps that need to be taken to further the interest of the industry have been discussed along with SWOT analysis of the industry.
Financials of CIL and its subsidiaries have been presented.

Table of Contents :-

Chapter 1 Introduction
1.1 Coal formation
1.2 Types of coal
1.3 Importance of coal
1.4 Uses of coal

Chapter 2 Coal mining methods
2.1 Surface mining
2.2 Underground mining
2.2.1 Room and Pillar method
2.2.2 Longwall Mining method
2.3 Coal mining methods in India

Chapter 3 Coal mining in India
3.1 Evolution
3.1.1 Nationalization on coal mines
3.2 Current industry structure

Chapter 4 Industry characteristics
4.1 Highly regulated
4.2 Monopolistic
4.3 Inelastic demand
4.4 Seasonal supply
4.5 Highly risky
4.6 Environmental issue
4.7 Duty structure

Chapter 5 Regulations
5.1 Coal distribution
5.1.1 Current coal distribution policy
5.1.2 Coal distribution prior to October 2007
5.2 Coal pricing & trade

Chapter 6 Global demand supply position
6.1 Global supply
6.1.1 World coal reserves
6.1.2 World coal production
6.2 World coal consumption
6.3 Major coal exporting/importing countries

Chapter 7 Domestic coal supply
7.1 Domestic coal reserve
7.2 Type wise & category-wise coal resources
7.3 Major coal producers in India

Chapter 8 Domestic coal demand
8.1 Offtake of coal
8.2 Sector -wise coal offtake
8.2.1 Demand from power sector
8.2.2 Demand from steel sector
8.2.3 Demand from cement sector
8.3 Import of coal
8.3.1 Coking coal imports
8.3.2 Non coking coal imports
8.4 Export of coal
8.5 Coal logistics
8.5.1 Modes of coal transportation
8.5.2 Cargo handling at Indian ports- Coal
8.5.3 Transportation cost

Chapter 9 Industry outlook
9.1 Demand projection
9.1.1 Projected coal requirement of the power sector
9.1.2 Projected coal requirement of the steel sector
9.1.3 Projected coal requirement of the cement sector
9.1.4 Total coal requirement of all sectors
9.2 Demand vis-à-vis availability as per ‘Coal Vision 2025’
9.3 Demand vis-à-vis availability as per ‘Expert committee road map on coal sector reforms’

Chapter 10 Challenges & Road Ahead
10.1 Meeting demand-supply gap
10.2 Bringing better technology
10.3 Promoting clean coal technologies
10.3.1 Coal beneficiation
10.3.2 CBM related activities
10.3.3 Underground coal gasification (UCG) related activities
10.3.4 Coal liquefaction related activities
10.4 Reducing coal cost
10.5 Improving mine safety
10.6 SWOT analysis of the industry

Chapter 11 Major players

Annexure I Definition
Annexure II State-wise distribution of coal reserve
Annexure III Grades of coal
Annexure IV Trends of fatal & serious accidents in CIL coal mines in India
Annexure V Labour productivity
Annexure VI Sector-wise allocation of coal blocks (Dec 07)
Annexure VII Abbreviations

List of Figures :-

Figure 1.1 Formation of coal
Figure 1.2 Types of coal
Figure 1.3 Price predictability
Figure 1.4 Prime energy consumption
Figure 2.1 Coal mining methods
Figure 2.2 Room & Pillar mining
Figure 2.3 Longwall mining
Figure 3.1 Industry structure
Figure 4.1 Pit head closing stock of raw coal FY07
Figure 4.2 Trends in custom duty & Import of non-coking coal
Figure 4.3 Trends in custom duty & import of coking coal
Figure 5.1 Domestic coal price
Figure 6.1 Estimated recoverable coal reserves
Figure 6.2 Major coal producing countries
Figure 6.3 Major coal consuming countries
Figure 6.4 World coking coal export growth
Figure 6.5 Major HCC/ SSCC Suppliers (2000-2006)
Figure 6.6 Major coking coal exporters
Figure 7.1 Geographical distribution of coal reserves in India
Figure 7.2 Coal & Lignite resource in India
Figure 7.3 Proved coal reserves in India
Figure 7.4 Trend in production of coking & non – coking Coal
Figure 7.5 Source-wise coal production
Figure 8.1 Sector-wise offtake of coal
Figure 8.2 Mode-wise breakup of installed capacity & electricity generation in India FY 08
Figure 8.3 Offtake of coal to the power sector
Figure 8.4 Domestic crude steel production & coal offtake to the steel sector
Figure 8.5 Total import of coking coal in India
Figure 8.6 Total Coal imports
Figure 8.7 Indian metallurgical coal imports by source FY07
Figure 8.8 Indian non-coking coal imports by source FY07
Figure 8.9 China’s coal exports & imports
Figure 8.10 Modes of coal transportation in India
Figure 8.11 Type-wise coal handled at the Indian ports
Figure 11.1 Total annual production of CIL subsidiaries
Figure 11.2 Annual production of CIL subsidiaries by type of mine
Figure 11.3 Labour productivity of CIL subsidiaries
Figure 11.4 PAT of CIL subsidiaries

List of Tables :-
Table 1.1 Sustained availability
Table 1.2 Percentage of Coal–based electricity generation out of total electricity generated.
Table 3.1 Company –wise production for FY08
Table 4.1 Comparison of coal v/s other fuels
Table 4.2 Duty structure on imported coal FY09
Table 6.1 World recoverable/ proved Coal Reserve
Table 6.2 World coal production
Table 6.3 World coal consumption
Table 7.1 Coal reserves of India
Table 7.2 Type-wise and category-wise coal resources
Table 8.1 Sector-wise offtake of coal
Table 8.2 Indonesia ‘s coal export potential
Table 8.3 South Africa coal export potential
Table 8.4 Australia’s coal export potential
Table 8.5 Coal exports from India
Table 8.6 Coal traffic at major ports in India
Table 8.7 The average turnaround time for coal at the major ports in India
Table 9.1 Crude steel production (National Steel Policy)
Table 9.2 Projected non-coking demand from non captive power utilities
Table 9.3 Projected non-coking demand from captive power utilities
Table 9.4 Projected requirements of coking coal of the steel sector
Table 9.5 Non-coking coal demand from sponge iron producers (FY03-07)
Table 9.6 Projected requirements of non-coking coal by the sponge iron producers
Table 9.7 Projected non-coking coal requirement of cement sector
Table 9.8 Total coal requirement of all sectors
Table 9.9 Demand vis-à-vis Availability as per ‘Coal Vision 2025’
Table 9.10 Demand vis-à-vis Availability as per the Expert Committee on Road Map for Coal Sector Reforms
Table 10.1 Present Coal Beneficiation Capacity
Table 11.1 Bharat Coking Coal Ltd. (BCCL) Financials
Table 11.2 Eastern Coalfields Ltd. (ECL) Financials
Table 11.3 Central Coalfields Ltd. (CCL) Financials
Table 11.4 Northern Coalfield Ltd. (NCL) Financials
Table 11.5 Western Coalfields Ltd. (WCL) Financials
Table 11.6 South Eastern Coalfields Ltd. (SECL) Financials
Table 11.7 Mahanadi Coalfields Ltd. (MCL) Financials
Table 11.8 North Eastern Coalfields Ltd. (NEC) / CIL Financials
Table 11.9 Singareni Collieries Company Ltd. (SCCL) Financials

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INTRODUCTION OVERVIEW
This study covers the world outlook for hydrated lime across more than 200 countries. For each year reported, estimates are given for the latent demand, or potential industry earnings (P.I.E.), for the country in question (in millions of U.S. dollars), the percent share the country is of the region and of the globe. These comparative benchmarks allow the reader to quickly gauge a country vis-à-vis others. Using econometric models which project fundamental economic dynamics within each country and across countries, latent demand estimates are created. This report does not discuss the specific players in the market serving the latent demand, nor specific details at the product level. The study also does not consider short-term cyclicalities that might affect realized sales. The study, therefore, is strategic in nature, taking an aggregate and long-run view, irrespective of the players or products involved.

This study does not report actual sales data (which are simply unavailable, in a comparable or consistent manner in virtually all of the 230 countries of the world). This study gives, however, my estimates for the worldwide latent demand, or the P.I.E., for hydrated lime. It also shows how the P.I.E. is divided across the world’s regional and national markets. For each country, I also show my estimates of how the P.I.E. grows over time (positive or negative growth). In order to make these estimates, a multi-stage methodology was employed that is often taught in courses on international strategic planning at graduate schools of business.

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Baby Food in Pakistan to 2010 is a detailed information resource covering all the key data points on Baby Food in Pakistan. It includes comprehensive value volume segmentation and market share data. The databook supplies actual data to 2005 and full forecasts to 2010.

Scope of this report

Contains information on 5 categories: Baby cereals, Baby snacks, Bottled baby food, Canned baby food & Other baby foods.
Provides market value, volume, expenditure and consumption data by market, segment and subsegment.
Includes company and brand share data by category, as well as distribution channel data.
Contains market value segmentation by demographic and socioeconomic group.
Research and analysis highlights

The market for Baby Food in Pakistan increased between 2000-2005, growing at an average annual rate of 5.4%.

The leading company in the market in 2005 was Nestle S.A.. The second-largest player was Royal Numico.

Key reasons to read Baby Food in Pakistan to 2010 :

Discover the major quantitative trends affecting the Baby Food markets.
Understand consumers’ consumption and expenditure patterns.
Understand the future direction of the market with reliable historical data and full five year forecasting.

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